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The blockchain concept forms the backbone of a new wave technology that promises to be deployed extensively in a wide variety of industrial and societal applications. Governments, financial institutions, banks, industrial supply chains,…
In digital learning systems, gaming the system refers to occasions when students attempt to succeed in an educational task by systematically taking advantage of system features rather than engaging meaningfully with the content. Often…
Despite some promising results in federated learning using game-theoretical methods, most existing studies mainly employ a one-level game in either a cooperative or competitive environment, failing to capture the complex dynamics among…
The predominant centralized paradigm in educational data management currently suffers from several critical issues such as vulnerability to malicious tampering, a high prevalence of diploma counterfeiting, and the onerous cost of…
In this innovative practice work-in-progress paper, we compare two different methods to teach machine learning concepts to undergraduate students in Electrical Engineering. While machine learning is now being offered as a senior-level…
For serious games on education, understanding the effectiveness of different learning methods in influencing cognitive processes remains a significant challenge. This study investigates the impact of serious games on graph structure…
Nowadays, engineers need to tackle many unprecedented challenges that are often complex, and, most importantly, cannot be exhaustively compartmentalized into a single engineering discipline. In other words, most engineering problems need to…
The rapid evolution of technology in educational settings has opened new avenues for enhancing learning experiences, particularly in specialized fields like network management. This paper explores the novel integration of a GenAI-based…
Access control is a critical component of computer security, governing access to system resources. However, designing policies and roles in traditional access control can be challenging and difficult to maintain in dynamic and complex…
Problem-based learning (PBL) is a constructivist learner-centered instructional approach based on the analysis, resolution and discussion of a given problem. It can be applied to any subject, indeed it is especially useful for the teaching…
This paper presents an innovative pedagogical framework employing tangible interactive games to enhance artificial intelligence (AI) knowledge and literacy among elementary education students. Recognizing the growing importance of AI…
Artificial Intelligence (AI), especially cloud platforms and large language models (LLMs), is changing how engineering is taught by making learning more interactive and flexible. However, in electrical engineering and energy systems,…
Project-based learning is recognized as an effective approach for improving engagement and applied understanding in STEM education. In quantum engineering courses, however, the question is no longer only whether students benefit from…
Federated Learning (FL) has gained widespread popularity in recent years due to the fast booming of advanced machine learning and artificial intelligence along with emerging security and privacy threats. FL enables efficient model…
In the context of higher education's evolving dynamics post-COVID-19, this paper assesses the impact of new pedagogical incentives implemented in a first-year undergraduate computing module at University College London. We employ a mixed…
Due to the distributed nature of federated learning (FL), the vulnerability of the global model and the need for coordination among many client devices pose significant challenges. As a promising decentralized, scalable and secure solution,…
Most of today's educators are in no shortage of digital and online learning technologies available at their fingertips, ranging from Learning Management Systems such as Canvas, Blackboard, or Moodle, online meeting tools, online homework,…
With the increasing artificial intelligence application, deep neural network (DNN) has become an emerging task. However, to train a good deep learning model will suffer from enormous computation cost and energy consumption. Recently,…
Agile methods are receiving a growing interest from industry and these approaches are nowadays well accepted and deployed in software engineering. However, some issues remain to introduce agility in systems engineering. The objective of…
In the past few years, Deep Reinforcement Learning (DRL) has become a valuable solution to automatically learn efficient resource management strategies in complex networks. In many scenarios, the learning task is performed in the Cloud,…